Fatty Acid-Binding Proteins Identification during the Evolution of Metabolic Syndrome: A Raman Spectroscopy-Based Approach.

Excess fat in abdominal deposits is a risk factor for multiple conditions, including metabolic syndrome (MetS); lipid metabolism plays an essential role in these pathologies; fatty acid-binding proteins (FABPs) are dedicated to the cytosolic transport of fat. FABP4, whose primary source is adipose tissue, is released into the circulation, acting as an adipokine, while FABP5 also accompanies the adverse effects of MetS. FABP4 and 5 are potential biomarkers of MetS, but their behavior during syndrome evolution has not been determined. Raman spectroscopy has been applied as an alternative method to disease biomarker detection. In this work, we detected spectral changes related to FABP4 and 5 in the serum at different points of time, using an animal model of a high-fat diet-induced MetS. FABP4 and 5 spectral changes show a contribution during the evolution of MetS, which indicates alteration to a molecular level that predisposes to established MetS. These findings place FABPs as potential biomarkers of MetS and Raman spectroscopy as an alternative method for MetS assessment.

Response to Comment on "Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes".

This letter aims to reply to Bratchenko and Bratchenko's comment on our paper "Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes." Our paper analyzed the feasibility of using in vivo Raman measurements combined with machine learning techniques to screen diabetic and prediabetic patients. We argued that this approach yields high overall accuracy (94.3%) while retaining a good capacity to distinguish between diabetic (area under the receiver-operating curve [AUC] = 0.86) and control classes (AUC = 0.97) and a moderate performance for the prediabetic class (AUC = 0.76). Bratchenko and Bratchenko's comment focuses on the possible overestimation of the proposed classification models and the absence of information on the age of participants. In this reply, we address their main concerns regarding our previous manuscript.

Structural Analysis of Carbon Fiber 3D-Printed Ribs for Small Wind Turbine Blades.

This work provides a structural analysis of small-scale 3D-printed wind turbine ribs subjected to compression. The ribs were manufactured according to NACA 23015 and NACA 633618 geometries, with polylactic acid (PLA) and polylactic acid with carbon fiber additives (CF-PLA). In addition, holes were manufactured into the sample bodies by either 3D printing or drilling for being compared with solid samples. The compression testing was performed by following the ASTM 695D standard, whereas the beginning and propagation of delamination were assessed with the ASTM 5528 standard. Experimental results revealed that 3D-printed built-in holes provided higher compression strength, hence higher structural efficiency, than the drilled samples. Significant improvement by adding carbon fiber additives into the PLA resin system in comparison to raw PLA was detected for at least one of the studied airfoil profiles. NACA geometries also represented a key parameter for avoiding stress concentration areas, as the FEM modeling supported. However, in damaged areas, fracture mechanisms were observed such as bead-bridging, which is a key parameter in reinforcing and consolidating the specimen bodies. Working in better interphase bonding and different additives between beads and layers is highly suggested for future studies.

Feasibility of Raman spectroscopy as a potential in vivo tool to screen for pre-diabetes and diabetes.

In this article, we investigated the feasibility of using Raman spectroscopy and multivariate analysis method to noninvasively screen for prediabetes and diabetes in vivo. Raman measurements were performed on the skin from 56 patients with diabetes, 19 prediabetic patients and 32 healthy volunteers. These spectra were collected along with reference values provided by the standard glycated hemoglobin (HbA1c) assay. A multiclass principal component analysis and support vector machine (PCA-SVM) model was created from the labeled Raman spectra and was validated through a two-layer cross-validation scheme. Classification accuracy of the model was 94.3% with an area under the receiver operating characteristic curve AUC of 0.76 (0.65-0.84) for the prediabetic group, 0.86 (0.71-0.93) for the diabetic group and 0.97(0.93-0.99) for the control group. Our results suggest the feasibility of using Raman spectroscopy for the classification of prediabetes and diabetes in vivo.

Raman Spectroscopy Study of Skin Biopsies from Patients with Parkinson's Disease: Trends in Alpha-Synuclein Aggregation from the Amide I Region.

Parkinson's disease (PD) is one of the most common neurological pathologies with a high prevalence worldwide. PD is characterized by Lewy bodies, whose major component is the aggregates of α-synuclein (αSyn) protein. Interestingly, recent works have demonstrated that skin biopsy studies are a promising diagnostic tool for evaluating α-synucleinopathies. In this sense, this work focuses on the detection of αSyn in skin biopsies employing Raman spectroscopy, using three different approaches: (i) the in vitro Raman spectrum of α-synuclein, (ii) the ex vivo Raman spectra of human skin biopsies from healthy and Parkinson's disease patients, and (iii) theoretical calculations of the Raman spectra obtained from different model αSyn fragments using density functional theory (DFT). Significant differences in the intensity and location of Raman active frequencies in the amide I region were found when comparing healthy and PD subjects related to α-synuclein conformational changes and variations in their aggregation behavior. In samples from healthy patients, we identified well-known Raman peaks at 1655, 1664, and 1680 cm-1 associated with the normal state of the protein. In PD subjects, shifted Raman bands and intensity variations were found at 1650, 1670, and 1687 cm-1 associated with aggregated forms of the protein. DFT calculations reveal that the shape of the amide I Raman peak in model αSyn fragments strongly depends on the degree of aggregation. Sizable frequency shifts and intensity variations are found within the highly relevant 1600-1700 cm-1 domain, revealing the sensitivity of the amide I Raman band to the changes in the local atomic environment. Interestingly, we obtain that the presence of surrounding waters also affects the structure of the amide I band, leading to the appearance of new peaks on the low-frequency side and a notable broadening of the Raman spectra. These results strongly suggest that, through Raman spectroscopy, it is possible to infer the presence of aggregated forms of αSyn in skin biopsies, a result that could have important implications for understanding α-synuclein related diseases.

Raman Spectroscopy for Adipose Tissue Assessment in Rat Models of Obesity and Type 1 Diabetes.

Adipose tissue presents structural and functional changes in obesity and type 1 diabetes mellitus (T1DM). In obesity, the size and number of adipocytes and adipokine secretion increases. In T1DM, a loss of adipose tissue suggests changes in the metabolic activity of this tissue. A significant challenge is to find alternative noninvasive methods to evaluate molecular changes in adipose tissue related to obesity and T1DM. Recently, Raman spectroscopy and chemometrics techniques have emerged as a tool for biological tissue analysis. In this work, we propose the use of Raman spectroscopy to characterize spectral differences in adipose tissue from different rat groups (control, obese, and T1DM). The Raman spectra were analyzed using direct band analysis, ratiometric analysis, and chemometric methods (principal component analysis (PCA) and support vector machines (SVMs)). We found that the Raman spectra of obese rats showed significant spectral differences compared to control and diabetic groups related to fatty acids Raman bands. Also, the obese group has a significant decrease in the degree of unsaturation of lipids. The PCA-SVM models showed classification performance ranging from 71.43% to 71.79% accuracy for brown and white adipose tissue samples, respectively. In conclusion, the results demonstrate that Raman spectroscopy can be used as a nondestructive method to assess adipose tissue according to a metabolic condition.

El objeto de conocimiento en la investigación cualitativa: un asunto epistemológico / The object of knowledge in qualitative research: an epistemological matter / O objeto de conhecimento na pesquisa qualitativa: um assunto epistemológico

Resumen Introducción: Los procesos reflexivos e interrogativos necesarios para desarrollar preguntas de investigación cualitativas efectivas, pueden dar forma y dirección a un estudio, sin embargo; a menudo se subestiman. Las buenas preguntas de investigación no necesariamente producen una buena investigación, pero las preguntas mal concebidas o elaboradas probablemente crearán problemas que afectarán todas las etapas posteriores de un estudio. Objetivo: Este artículo aborda el desarrollo de preguntas de investigación y cómo los procesos de generación y refinación de preguntas son fundamentales para la conformación de un estudio cualitativo. Desarrollo: Generar preguntas de investigación relevantes y adecuadas requiere que el investigador preste atención no solo a las preguntas en sí mismas, sino a sus conexiones con todos los componentes del diseño; es decir, los objetivos a los que pueden responder las preguntas; las implicaciones para las preguntas relacionadas con su marco conceptual; los métodos que podría usar para responder las preguntas y las amenazas de validez que deberá abordar. Al igual que con los otros componentes del diseño, reflexionar sobre estos temas es una herramienta extremadamente útil para desarrollar sus preguntas. Conclusiones: En los estudios cualitativos, el proceso continuo de preguntas es una parte integral en la comprensión de las vidas y perspectivas de otros. Es importante enfatizar que este tipo de investigación requiere que el investigador asuma una postura epistemológica, seleccione un método y también elija ciertas técnicas que le permitan recopilar información en el trabajo de campo.

Abstract Introduction: Although frequently underestimated, reflexive and interrogative processes needed to develop the research questions in qualitative research, can give shape and direction to a study. Good research questions do not necessarily produce a good research study, but badly conceived or elaborated research questions can create problems which will further have impacts on all stages of the study. Objective: This study addresses the development of research questions and how their generation and refinement processes are fundamental in the conformation of a qualitative study. Development: Generating relevant and adequate research questions requires the researchers to give attention to the questions and their relations to all the components of the design; in other words; to the objectives, the conceptual framework, the methods used, the possible implications involved, the validity, etcetera. Reflecting on these issues is a useful tool while developing research questions. Conclusions: In qualitative studies, the ongoing process of questioning is integral to the comprehension of the lives and perspectives of others. So, it is important to emphasize that qualitative research requires the researchers to adopt an epistemological posture by selecting methods and procedures which can support their field work information gathering.

Resumo Introdução: Os processos reflexivos e interrogativos necessários para desenvolver perguntas de pesquisa qualitativas efetivas podem dar forma e direção a um estudo, porém frequentemente são subestimados. As boas perguntas de pesquisa não necessariamente produzem uma boa pesquisa, mas as perguntas mal concebidas ou elaboradas provavelmente criarão problemas que afetarão todas as etapas posteriores de um estudo. Objetivo: Este artigo aborda o desenvolvimento de perguntas de pesquisa e como os processos de produção e refinamento de preguntas são fundamentais para a conformação de um estudo qualitativo. Desenvolvimento: Gerar perguntas de pesquisa relevantes e adequadas requer que o pesquisador preste atenção não só às preguntas em si mesmas, senão a suas conexões com todos os componentes do desenho: quer dizer, os objetivos aos que podem responder as preguntas; as implicações para as preguntas relacionadas com seu marco conceptual; os métodos que poderia usar para responder as perguntas e as ameaças de validade que deverá abordar. Ao igual que com os outros componentes do desenho, refletir sobre estes temas é uma ferramenta extremadamente útil para desenvolver suas perguntas. Conclusões: Nos estudos qualitativos, o processo contínuo de perguntas é uma parte integral na compreensão das vidas e perspectivas de outros. É importante enfatizar que este tipo de pesquisa, requer que o pesquisador assuma uma postura epistemológica, selecione um método e também eleja certas técnicas que lhe permitam recopilar informação no trabalho de campo.

Raman Spectroscopy and Chemometric Modeling to Predict Physical-Chemical Honey Properties from Campeche, Mexico.

In this work, 10 chemometric models based on Raman spectroscopy were constructed to predict the physicochemical properties of honey produced in the state of Campeche, Mexico. The properties of honey studied were pH, moisture, total soluble solids (TSS), free acidity, lactonic acidity, total acidity, electrical conductivity, Redox potential, hydroxymethylfurfural (HMF), and ash content. These proprieties were obtained according to the methods described by the Association of Official Analytical Chemists, Codex Alimentarius, and the International Honey Commission. For the construction of the chemometric models, 189 honey samples were collected and analyzed in triplicate using Raman spectroscopy to generate the matrix data [X], which were correlated with each of the physicochemical properties [Y]. The predictive capacity of each model was determined by cross validation and external validation, using the statistical parameters: standard error of calibration (SEC), standard error of prediction (SEP), coefficient of determination of cross-validation (R2cal), coefficient of determination for external validation (R2val), and Student's t-test. The statistical results indicated that the chemometric models satisfactorily predict the humidity, TSS, free acidity, lactonic acidity, total acidity, and Redox potential. However, the models for electric conductivity and pH presented an acceptable prediction capacity but not adequate to supply the conventional processes, while the models for predicting ash content and HMF were not satisfactory. The developed models represent a low-cost tool to analyze the quality of honey, and contribute significantly to increasing the honey distribution and subsequently the economy of the region.

Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools: reply to comment.

We show the spectra of advanced glycation products in response to recent comments made by Bratchenko et al. Our results suggest that information retrieved by Raman spectroscopy is relevant to screening diabetic patients, however, the comparison carried out in our paper, between ANN and SVM, was not fair, because of the erroneous PCA selection procedure and different sources of variation present in the analysis.

Improved Vancouver Raman Algorithm Based on Empirical Mode Decomposition for Denoising Biological Samples.

A novel method based on the Vancouver Raman algorithm (VRA) and empirical mode decomposition (EMD) for denoising Raman spectra of biological samples is presented. The VRA is one of the most used methods for denoising Raman spectroscopy and is composed of two main steps: signal filtering and polynomial fitting. However, the signal filtering step consists in a simple mean filter that could eliminate spectrum peaks with small intensities or merge relatively close spectrum peaks into one single peak. Thus, the result is often sensitive to the order of the mean filter, so the user must choose it carefully to obtain the expected result; this introduces subjectivity in the process. To overcome these disadvantages, we propose a new algorithm, namely the modified-VRA (mVRA) with the following improvements: (1) to replace the mean filter step by EMD as an adaptive parameter-free signal processing method; and (2) to automate the selection of polynomial degree. The denoising capabilities of VRA, EMD, and mVRA were compared in Raman spectra of artificial data based on Teflon material, synthetic material obtained from vitamin E and paracetamol, and biological material of human nails and mouse brain. The correlation coefficient (ρ) was used to compare the performance of the methods. For the artificial Raman spectra, the denoised signal obtained by mVRA (ρ>0.91) outperforms VRA (ρ>0.86) for moderate to high noise levels whereas mVRA outperformed EMD (ρ>0.90) for high noise levels. On the other hand, when it comes to modeling the underlying fluorescence signal of the samples (i.e., the baseline trend), the proposed method mVRA showed consistent results (ρ>0.94). For Raman spectra of synthetic material, good performance of the three methods (ρ=0.99 for VRA, ρ=0.93 for EMD, and ρ=0.99 for mVRA) was obtained. Finally, in the biological material, mVRA and VRA showed similar results (ρ=0.96 for VRA, ρ=0.85 for EMD, and ρ=0.91 for mVRA); however, mVRA retains valuable information corresponding to relevant Raman peaks with small amplitude. Thus, the application of EMD as a filter in the VRA method provides a good alternative for denoising biological Raman spectra, since the information of the Raman peaks is conserved and parameter tuning is not required. Simultaneously, EMD allows the baseline correction to be automated.

Use of Raman spectroscopy in the assessment of skin after CO2 ablative fractional laser surgery on acne scars.

BACKGROUND: Ablative fractional laser surgery is a common technique for treating acne scars. However, an in vivo and noninvasive analysis of the histologic variations between acne skin and the resulting resurfaced skin is needed in order to evaluate the wound healing process of the scars induced by the ablative fractional laser surgery. MATERIALS AND METHODS: Nine patients with acne scars underwent a single treatment with a CO2 ablative fractional laser surgery. Collagen presence on the resurfaced skin was noninvasively assessed by means of Raman spectroscopy and principal component analysis. RESULTS: Principal component analysis shows that all the patients presented a collagen regeneration on the resurfaced skin after the laser treatment. CONCLUSION: Collagen plays a crucial role in the wound healing process. By assessing the collagen presence on the skin, it was possible to quantify the regenerative effects of the ablative fractional laser in a noninvasive way.

Surface-enhanced raman spectroscopy: A non invasive alternative procedure for early detection in childhood asthma biomarkers in saliva.

The early detection of bronchial inflammation in asthma, through a non-invasive, simple method and under a subclinical state, could lead to a more effective control of this condition. The aim of this study was to identify biomarkers of bronchial inflammation in the saliva of children with asthma through immunoassay and Surface Enhanced Raman Spectroscopy (SERS). We conducted an analytical cross-sectional study in 44 children ages 6-12; the diagnosis of asthma was made according to Global Initiative for Asthma (GINA) standards. The children's saliva was analyzed by immunoassay for the quantification of 37 cytokines, as well as SERS analysis in a confocal Raman microscope at 785 nm. We found a significant association between bronchial obstruction and IL-8 (p = 0.004), IL-10 (p = 0.008) and sCD163 (p = 0.003). The Raman spectra showed significant amplification in the region of 760 to 1750 cm-1. The Principal Component Analysis and Linear Discriminant Analysis (PCA-LDA) method has a sensitivity of 85%, specificity of 82% and an accuracy of 84% for the diagnosis of asthma. These results demonstrate the presence of a subclinical inflammatory state, suggestive of bronchial remodeling in the population studied. The SERS method is a potential tool for identifying bronchial inflammation and its endotype, allowing for a highly sensitive and specific diagnosis.

Detection of hydroquinone by Raman spectroscopy in patients with melasma before and after treatment.

BACKGROUND: Melasma is an acquired, facial hyperpigmentation without a specific origin. It is regularly associated with multiple etiologic factors such as pregnancy, genetic, racial, and from estrogen administration. Among the methods to treat skin hyperpigmentation a series of skin bleaching agents have been used. At present, the most commonly used agent is known as hydroquinone. Nowadays, it is known that hydroquinone can cause cancer in animals with unknown relevance to humans. MATERIAL AND METHODS: In this work, Raman spectroscopy was used to observe the presence of hydroquinone in the skin of 18 patients who have been under treatment for melasma. RESULTS: A significant increase in the Raman signal was observed in the six bands associated with hydroquinone after melasma treatment. CONCLUSION: The authors believe that monitoring the presence of hydroquinone may be useful for an optimal personalized treatment of melasma and to provide the specialist a support tool to control the administration of this type of bleaching agents.

Use of Raman spectroscopy to screen diabetes mellitus with machine learning tools.

Type 2 diabetes mellitus (DM2) is one of the most widely prevalent diseases worldwide and is currently screened by invasive techniques based on enzymatic assays that measure plasma glucose concentration in a laboratory setting. A promising plan of action for screening DM2 is to identify molecular signatures in a non-invasive fashion. This work describes the application of portable Raman spectroscopy coupled with several supervised machine-learning techniques, to discern between diabetic patients and healthy controls (Ctrl), with a high degree of accuracy. Using artificial neural networks (ANN), we accurately discriminated between DM2 and Ctrl groups with 88.9-90.9% accuracy, depending on the sampling site. In order to compare the ANN performance to more traditional methods used in spectroscopy, principal component analysis (PCA) was carried out. A subset of features from PCA was used to generate a support vector machine (SVM) model, albeit with decreased accuracy (76.0-82.5%). The 10-fold cross-validation model was performed to validate both classifiers. This technique is relatively low-cost, harmless, simple and comfortable for the patient, yielding rapid diagnosis. Furthermore, the performance of the ANN-based method was better than the typical performance of the invasive measurement of capillary blood glucose. These characteristics make our method a promising screening tool for identifying DM2 in a non-invasive and automated fashion.

A Semi-Pilot Photocatalytic Rotating Reactor (RFR) with Supported TiO2/Ag Catalysts for Water Treatment.

A four stage semi-pilot scale RFR reactor with ceramic disks as support for TiO2 modified with silver particles was developed for the removal of organic pollutants. The design presented in this article is an adaptation of the rotating biological reactors (RBR) and its coupling with the modified catalyst provides additional advantages to designs where a catalyst in suspension is used. The optimal parameter of rotation was 54 rpm and the submerged surface of the disks offer a total contact area of 387 M². The modified solid showed a decrease in the value of its bandgap compared to commercial titanium. The system has a semi-automatic operation with a maximum reaction time of 50 h. Photo-activity tests show high conversion rates at low concentrations. The results conform to the Langmuir heterogeneous catalysis model.

Evaluation of liver fibrosis using Raman spectroscopy and infrared thermography: A pilot study.

Liver fibrosis is a pathological process that can escalate to cirrhosis and then liver failure, a major public health concern that affect hundreds of millions of people in both developed and developing countries. Detection of liver fibrosis during its earlier stages is a matter of great importance which may allow prevention of development of cirrhosis in patients with chronic liver disease. In this work, Raman spectroscopy and thermography were evaluated to detect early pathological signs of liver fibrosis in rats in which liver fibrosis was induced using carbon tetrachloride. Results show that Raman spectra of healthy and fibrotic livers significantly differ among each other and can be classified by principal component analysis and discriminant analysis. The PCA-LDA method has a sensitivity of 100%, specificity 85% and diagnostic accuracy of 93.5%. Thermography also revealed characteristic temperature patterns for fibrotic livers compared to healthy livers. Current data suggest that Raman spectroscopy and thermography could be used to detect fibrosis in ex vivo liver samples.

Proceso de enfermería; lo que sí es y lo que no es / Nursing process; what it is and what is not

En esta reflexión nos centraremos exclusivamente en los aspectos relacionados con lo que es y no es el proceso de enfermería; puesto que las imprecisiones, omisiones o excesos en torno a este, conllevan, inevitablemente, a imprecisiones, omisiones o excesos en la disciplina de enfermería. El propósito es poner de manifiesto dichas imprecisiones, así como las consecuencias que estas pueden tener en la profesión y en la disciplina. La ciencia de enfermería se basa en un amplio marco teórico; su arte radica en las habilidades del cuidado y capacidades de cada enfermera. Los profesionales de esta área reconocen la necesidad de que sus practicantes deben actuar profesionalmente y ser responsables de la atención que ofrecen. Para asegurar la planificación y entrega efectiva de los cuidados de enfermería, los profesionales han adoptado un enfoque estructurado llamado « proceso de enfermería ¼

Fluorescence background removal method for biological Raman spectroscopy based on empirical mode decomposition.

Raman spectroscopy of biological tissue presents fluorescence background, an undesirable effect that generates false Raman intensities. This paper proposes the application of the Empirical Mode Decomposition (EMD) method to baseline correction. EMD is a suitable approach since it is an adaptive signal processing method for nonlinear and non-stationary signal analysis that does not require parameters selection such as polynomial methods. EMD performance was assessed through synthetic Raman spectra with different signal to noise ratio (SNR). The correlation coefficient between synthetic Raman spectra and the recovered one after EMD denoising was higher than 0.92. Additionally, twenty Raman spectra from skin were used to evaluate EMD performance and the results were compared with Vancouver Raman algorithm (VRA). The comparison resulted in a mean square error (MSE) of 0.001554. High correlation coefficient using synthetic spectra and low MSE in the comparison between EMD and VRA suggest that EMD could be an effective method to remove fluorescence background in biological Raman spectra.

Raman spectroscopy analysis of the skin of patients with melasma before standard treatment with topical corticosteroids, retinoic acid, and hydroquinone mixture.

BACKGROUND: Melasma is an abnormal acquired hyperpigmentation of the face of unknown origin, it is considered a single disease and very little has been found regarding its pathogenesis. It is usually assumed that melasma is due to excessive melanin production, but previous work using Raman spectroscopy showed degraded molecules of melanin in some melasma subjects, which may help to explain the success or failure of the standard therapy. METHODS: We perform Raman spectroscopy measurements on in vivo skin from melasma patients before treatment to identify the molecular structure of melanin within every melasma lesion. The Raman spectra were grouped according to the treatment response from patient, and the Raman spectra were analyzed. RESULTS: Raman spectroscopy measurements showed a different molecular structure of the patients who did not respond to treatment, those patients shows atypical Raman skin spectrum with peaks associated with melanin not well defined, which is consistent with molecular degradation and protein breakdown. CONCLUSION: Our results are consistent with our previous work in the sense that melasma patients who do not respond to treatment have an abnormal melanin. We believe it will eventually help to decide the treatment of melasma in clinical dermatology.